Dynamic and quantitative characterization of antagonism within disinfectant mixtures by a modified area-concentration ratio method

Beneficial or harmful: Time-dependent hormesis induced by typical disinfectants and their mixtures with toxicological interaction

Disinfectants and their mixtures can induce hormesis. However, how the mixture hormesis is related to those of components and the interactions in disinfectant mixtures remain unclear. In this paper, the luminescence inhibition toxicities of chlorinated sodium phosphate (CSP), dodecyl dimethyl benzyl ammonium bromide (DOB), dodecyl dimethyl benzyl ammonium chloride (DOC), ethanol (EtOH), glutaraldehyde (GLA), hydrogen peroxide (H2O2), isopropyl alcohol (IPA), n-propanol (NPA), and 20 mixture rays in four mixture systems (EtOH-H2O2, DOB-H2O2, DOC-EtOH, and EtOH-IPA-NPA) containing at least one component showing hormesis to Vibrio qinghaiensis sp.-Q67 (Q67) were determined at 0.25, 3, 6, 9, and 12 h. The synergism-antagonism heatmap based on independent action model (noted as SAHmapIA) was developed to systematically evaluate the interactions in various mixtures. It was shown that five disinfectants (CSP, EtOH, H2O2, NPA, and IPA) and 17 mixture rays exhibited time-dependent hormesis. The hormetic component was responsible for the hormesis of the mixture rays. Most mixture rays showed low- concentration/dose additive action and high-concentration/dose synergism at different time. This study further exemplified the interrelationship between the hormesis in the mixtures and their components and implied the need to pay attention to the time-dependent hormesis and interactions induced by the disinfectants.

A novel equal frequency sampling of factor levels (EFSFL) method is applied to identify the dominant factor inducing the combined toxicities of 13 factors

The research framework combining global sensitivity analysis (GSA) with quantitative high-throughput screening (qHTS), called GSA-qHTS, provides a potentially feasible way to screen for important factors that induce toxicities of complex mixtures. Despite its value, the mixture samples designed using the GSA-qHTS technique still have a shortage of unequal factor levels, which leads to an asymmetry in the importance of elementary effects (EEs). In this study, we developed a novel method for mixture design that enables equal frequency sampling of factor levels (called EFSFL) by optimizing both the trajectory number and the design and expansion of the starting points for the trajectory. The EFSFL has been successfully employed to design 168 mixtures of 13 factors (12 chemicals and time) that each have three levels. By means of high-throughput microplate toxicity analysis, the toxicity change rules of the mixtures are revealed. Based on EE analysis, the important factors affecting the toxicities of the mixtures are screened. It was found that erythromycin is the dominant factor and time is an important non-chemical factor in mixture toxicities. The mixtures can be classified into types A, B, and C mixtures according to their toxicities at 12 h, and all the types B and C mixtures contain erythromycin at the maximum concentration. The toxicities of the type B mixtures increase firstly over time (0.25 ∼ 9 h) and then decrease (12 h), while those of the type C mixtures consistently increase over time. Some type A mixtures produce stimulation that increases with time. With the present new approach to mixture design, the frequency of factor levels in mixture samples is equal. Consequently, the accuracy of screening important factors is improved based on the EE method, providing a new method for the study of mixture toxicity.